ing with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Publications Dept, ACM Inc., fax +1 (212) 869-0481, or permissions@acm.org. Which GOMS? p. 2 2 Keywords: GOMS, cognitive modeling, usability engineering ABSTRACT Since the seminal Card, Moran, & Newell (1983) book, The psychology of human-computer interaction, the GOMS model has been one of the few widely known theoretical concepts in human-computer interaction. This concept has spawned much research to verify and extend the original work and has been used in real-world design and evaluation situations. This paper synthesizes the previous work on GOMS to provide an integrated view of GOMS models and how they can be used in design. We briefly describe the major variants of GOMS that have matured sufficiently to be used in actual design. We then provide guidance to practitioners about which GOMS var...

In this paper, we explore the question of whether program understanding tools enhance or change the way that programmers understand programs. The strategies that programmers use to comprehend programs vary widely. Program understanding tools should enhance or ease the programmer's preferred strategies, rather than impose a fixed strategy that may not always be suitable. We present observations from a user study that compares three tools for browsing program source code and exploring software structures. In this study, 30 participants used these tools to solve several high-level program understanding tasks. These tasks required a broad range of comprehension strategies. We describe how these tools supported or hindered the diverse comprehension strategies used.

Social resources like trust and shared identity make it easier for people to work and play together. Such social resources are sometimes referred to as social capital. Thirty years ago, Americans built social capital as a side effect of participation in civic organizations and social activities, including bowling leagues. Today, they do so far less frequently (Putnam 2000). HCI researchers and practitioners need to find new ways for people to interact that will generate even more social capital than bowling together does. A new theoretical construct, SocioTechnical Capital, provides a framework for generating and evaluating technology-mediated social relations.

The paper argues that new approaches for delivering HCI knowledge from theory to designers will be necessary in the new millennium. First the progress made developing cognitive theories of interaction and their impact on the design process is reviewed. Direct application of current cognitive theories to design has been limited by scalability problems. This has led to bridging models that attempt to deliver insights from theory to design models in a more tractable manner. However, these too have met with limited success. An alternative is to represent HCI knowledge as claims and adopt the task-artefact approach to design in which theories are embedded in well-designed artefacts and explained to designers as psychologically motivated design rationale. Claims are proposed as a possible bridging representation that may enable theories to frame appropriate recommendations for designers and, vice versa, enable designers to ask appropriate questions for theoretical research. However, claims provide design advice grounded in specific scenarios and examples, which 1 limits their generality. Hence claims are their associated artefacts needs to be generalised so

this article, NGOMSL, in which learning time and execution time are predicted based on a program-like representation of the procedures that the user must learn and execute to perform tasks with the system. NGOMSL is an acronym for Natural GOMS Language, which is a structured natural language used to represent the user's methods and selection rules. NGOMSL models thus have an explicit representation of the user's methods, which are assumed to be strictly sequential and hierarchical in form. The execution time for a task is predicted by simulating the execution of the methods required to perform the task. Each NGOMSL statement is assumed to require a small fixed time to execute, and any operators in the statement, such as a keystroke, will then take additional time depending on the operator. The time to learn how to operate the interface can be predicted from the length of the methods, and the amount of transfer of training from the number of methods or method steps previously learned. Thus estimating times for learning and execution both require counting the number of NGOMSL statements involved; details on this process will be provided in this article.

The current variety of alternative approaches to usability evaluation methods (UEMs) designed to assess and improve usability in software systems is offset by a general lack of understanding of the capabilities and limitations of each. Practitioners need to know which methods are more effective and in what ways and for what purposes. However, UEMs cannot be evaluated and compared reliably because of the lack of standard criteria for comparison. In this article, we present a practical discussion of factors, comparison criteria, and UEM performance measures useful in studies comparing UEMs. In demonstrating the importance of developing appropriate UEM evaluation criteria, we offer operational definitions and possible measures of UEM performance. We highlight specific challenges that researchers and practitioners face in comparing UEMs and provide a point of departure for further discussion and refinement of the principles and techniques used to approach UEM evaluation and comparison. 1.

The concept of affordance is popular in the HCI community but not well understood. Donald Norman appropriated the concept of affordances from James J. Gibson for the design of common objects and both implicitly and explicitly adjusted the meaning given by Gibson. There was, however, ambiguity in Norman’s original definition and use of affordances which he has subsequently made efforts to clarify. His definition germinated quickly and through a review of the HCI literature we show that this ambiguity has lead to widely varying uses of the concept. Norman has recently acknowledged the ambiguity, however, important clarifications remain. Using affordances as a basis, we elucidate the role of the designer and the distinction between usefulness and usability. We expand Gibson’s definition into a framework for design.

Current practice in Human Computer Interaction as encouraged by educational institutes, academic review processes, and institutions with usability groups advocate usability evaluation as a critical part of every design process. This is for good reason: usability evaluation has a significant role to play when conditions warrant it. Yet evaluation can be ineffective and even harmful if naively done ‘by rule ’ rather than ‘by thought’. If done during early stage design, it can mute creative ideas that do not conform to current interface norms. If done to test radical innovations, the many interface issues that would likely arise from an immature technology can quash what could have been an inspired vision. If done to validate an academic prototype, it may incorrectly suggest a design’s scientific worthiness rather than offer a meaningful critique of how it would be adopted and used in everyday practice. If done without regard to how cultures adopt technology over time, then today's reluctant reactions by users will forestall tomorrow's eager acceptance. The choice of evaluation methodology – if any – must arise from and be appropriate for the actual problem or research question under consideration. Author Keywords Usability testing, interface critiques, teaching usability.

We describe the use of a recommender system to enable continuous knowledge acquisition and individualized tutoring of application software across an organization. Installing such systems will result in the capture of evolving expertise and in organization-wide learning (OWL). We present the results of a year-long naturalistic inquiry into an application's usage patterns, based on logging users' actions. We analyze the data to develop user models, individualized expert models, and instructional indicators. We show how this information is used to recommend learning tips to users. Keywords Recommender system, organization-wide learning, OWL, individualized instruction, agent, instrumentation, logging. Introduction New Workplace Technologies Enable New Learning Methods In the last decade, an enormous change has taken place in the workplace: there is a PC on every desk, and much office work is performed in the medium of software. Mastering one's software - at least the portion of...

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